Overview

Dataset statistics

Number of variables98
Number of observations3556
Missing cells0
Missing cells (%)0.0%
Duplicate rows344
Duplicate rows (%)9.7%
Total size in memory618.7 KiB
Average record size in memory178.2 B

Variable types

Categorical94
Numeric4

Alerts

Dataset has 344 (9.7%) duplicate rowsDuplicates
Total.Fatal.Injuries is highly overall correlated with Total.UninjuredHigh correlation
Total.Uninjured is highly overall correlated with Total.Fatal.Injuries and 1 other fieldsHigh correlation
Number.of.Engines is highly overall correlated with Engine.Type_reciprocating and 2 other fieldsHigh correlation
Aircraft.damage_Destroyed is highly overall correlated with Aircraft.damage_SubstantialHigh correlation
Aircraft.damage_Substantial is highly overall correlated with Aircraft.damage_DestroyedHigh correlation
Amateur.Built_No is highly overall correlated with Amateur.Built_YesHigh correlation
Amateur.Built_Yes is highly overall correlated with Amateur.Built_NoHigh correlation
Engine.Type_reciprocating is highly overall correlated with Number.of.Engines and 1 other fieldsHigh correlation
Engine.Type_turbo fan is highly overall correlated with Total.Uninjured and 1 other fieldsHigh correlation
Engine.Type_turbo shaft is highly overall correlated with Engine.Type_reciprocatingHigh correlation
Engine.Type_unknown is highly overall correlated with Number.of.EnginesHigh correlation
Weather.Condition_IMC is highly overall correlated with Weather.Condition_VMCHigh correlation
Weather.Condition_VMC is highly overall correlated with Weather.Condition_IMCHigh correlation
Number.of.Engines is highly imbalanced (66.9%)Imbalance
Aircraft.damage_Minor is highly imbalanced (78.3%)Imbalance
Amateur.Built_No is highly imbalanced (64.9%)Imbalance
Amateur.Built_Yes is highly imbalanced (64.9%)Imbalance
Engine.Type_reciprocating is highly imbalanced (54.6%)Imbalance
Engine.Type_turbo fan is highly imbalanced (93.8%)Imbalance
Engine.Type_turbo jet is highly imbalanced (95.8%)Imbalance
Engine.Type_turbo prop is highly imbalanced (84.5%)Imbalance
Engine.Type_turbo shaft is highly imbalanced (75.5%)Imbalance
Engine.Type_unknown is highly imbalanced (85.6%)Imbalance
Purpose.of.flight_Aerial Application is highly imbalanced (73.2%)Imbalance
Purpose.of.flight_Aerial Observation is highly imbalanced (96.5%)Imbalance
Purpose.of.flight_Business is highly imbalanced (58.7%)Imbalance
Purpose.of.flight_Executive/corporate is highly imbalanced (89.5%)Imbalance
Purpose.of.flight_Ferry is highly imbalanced (86.0%)Imbalance
Purpose.of.flight_Flight Test is highly imbalanced (99.3%)Imbalance
Purpose.of.flight_Glider Tow is highly imbalanced (99.6%)Imbalance
Purpose.of.flight_Other Work Use is highly imbalanced (99.6%)Imbalance
Purpose.of.flight_Positioning is highly imbalanced (94.8%)Imbalance
Purpose.of.flight_Public Aircraft is highly imbalanced (98.5%)Imbalance
Purpose.of.flight_Public Aircraft - Federal is highly imbalanced (99.6%)Imbalance
Purpose.of.flight_Public Aircraft - Local is highly imbalanced (99.6%)Imbalance
Purpose.of.flight_Skydiving is highly imbalanced (99.6%)Imbalance
Weather.Condition_IMC is highly imbalanced (55.9%)Imbalance
Weather.Condition_UNK is highly imbalanced (88.7%)Imbalance
Weather.Condition_VMC is highly imbalanced (51.0%)Imbalance
Broad.phase.of.flight_Approach is highly imbalanced (50.3%)Imbalance
Broad.phase.of.flight_Climb is highly imbalanced (82.7%)Imbalance
Broad.phase.of.flight_Descent is highly imbalanced (82.2%)Imbalance
Broad.phase.of.flight_Go-around is highly imbalanced (88.1%)Imbalance
Broad.phase.of.flight_Standing is highly imbalanced (94.0%)Imbalance
Broad.phase.of.flight_Taxi is highly imbalanced (77.9%)Imbalance
Broad.phase.of.flight_Unknown is highly imbalanced (88.0%)Imbalance
States_AK is highly imbalanced (69.1%)Imbalance
States_AL is highly imbalanced (87.8%)Imbalance
States_AR is highly imbalanced (86.4%)Imbalance
States_AZ is highly imbalanced (77.9%)Imbalance
States_CO is highly imbalanced (81.8%)Imbalance
States_CT is highly imbalanced (94.8%)Imbalance
States_DC is highly imbalanced (99.3%)Imbalance
States_DE is highly imbalanced (98.7%)Imbalance
States_FL is highly imbalanced (68.9%)Imbalance
States_GA is highly imbalanced (83.9%)Imbalance
States_HI is highly imbalanced (96.7%)Imbalance
States_IA is highly imbalanced (88.8%)Imbalance
States_ID is highly imbalanced (89.9%)Imbalance
States_IL is highly imbalanced (81.8%)Imbalance
States_IN is highly imbalanced (88.5%)Imbalance
States_KS is highly imbalanced (88.1%)Imbalance
States_KY is highly imbalanced (90.9%)Imbalance
States_LA is highly imbalanced (84.9%)Imbalance
States_MA is highly imbalanced (91.8%)Imbalance
States_MD is highly imbalanced (93.6%)Imbalance
States_ME is highly imbalanced (95.2%)Imbalance
States_MI is highly imbalanced (83.7%)Imbalance
States_MN is highly imbalanced (87.3%)Imbalance
States_MO is highly imbalanced (83.4%)Imbalance
States_MS is highly imbalanced (91.8%)Imbalance
States_MT is highly imbalanced (88.0%)Imbalance
States_NC is highly imbalanced (87.0%)Imbalance
States_ND is highly imbalanced (93.0%)Imbalance
States_NE is highly imbalanced (90.9%)Imbalance
States_NH is highly imbalanced (95.2%)Imbalance
States_NJ is highly imbalanced (89.9%)Imbalance
States_NM is highly imbalanced (86.7%)Imbalance
States_NV is highly imbalanced (90.7%)Imbalance
States_NY is highly imbalanced (82.8%)Imbalance
States_OH is highly imbalanced (84.2%)Imbalance
States_OK is highly imbalanced (87.0%)Imbalance
States_OR is highly imbalanced (83.7%)Imbalance
States_PA is highly imbalanced (81.9%)Imbalance
States_PR is highly imbalanced (99.6%)Imbalance
States_RI is highly imbalanced (98.2%)Imbalance
States_SC is highly imbalanced (89.2%)Imbalance
States_SD is highly imbalanced (95.4%)Imbalance
States_TN is highly imbalanced (92.4%)Imbalance
States_TX is highly imbalanced (58.1%)Imbalance
States_UT is highly imbalanced (90.4%)Imbalance
States_VA is highly imbalanced (90.9%)Imbalance
States_VT is highly imbalanced (97.2%)Imbalance
States_WA is highly imbalanced (82.2%)Imbalance
States_WI is highly imbalanced (88.7%)Imbalance
States_WV is highly imbalanced (95.6%)Imbalance
States_WY is highly imbalanced (90.2%)Imbalance
Total.Uninjured is highly skewed (γ1 = 21.69111517)Skewed
Total.Fatal.Injuries has 2873 (80.8%) zerosZeros
Total.Serious.Injuries has 3104 (87.3%) zerosZeros
Total.Minor.Injuries has 2969 (83.5%) zerosZeros
Total.Uninjured has 1266 (35.6%) zerosZeros

Reproduction

Analysis started2023-06-01 11:54:14.669419
Analysis finished2023-06-01 11:54:56.704630
Duration42.04 seconds
Software versionpandas-profiling v0.0.dev0
Download configurationconfig.json

Variables

Number.of.Engines
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
1.0
2978 
2.0
486 
0.0
 
72
3.0
 
14
4.0
 
6

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters10668
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row2.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 2978
83.7%
2.0 486
 
13.7%
0.0 72
 
2.0%
3.0 14
 
0.4%
4.0 6
 
0.2%

Length

2023-06-01T13:54:56.799417image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:56.944178image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0 2978
83.7%
2.0 486
 
13.7%
0.0 72
 
2.0%
3.0 14
 
0.4%
4.0 6
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 3628
34.0%
. 3556
33.3%
1 2978
27.9%
2 486
 
4.6%
3 14
 
0.1%
4 6
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7112
66.7%
Other Punctuation 3556
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3628
51.0%
1 2978
41.9%
2 486
 
6.8%
3 14
 
0.2%
4 6
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 3556
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10668
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3628
34.0%
. 3556
33.3%
1 2978
27.9%
2 486
 
4.6%
3 14
 
0.1%
4 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3628
34.0%
. 3556
33.3%
1 2978
27.9%
2 486
 
4.6%
3 14
 
0.1%
4 6
 
0.1%

Total.Fatal.Injuries
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.39735658
Minimum0
Maximum27
Zeros2873
Zeros (%)80.8%
Negative0
Negative (%)0.0%
Memory size55.6 KiB
2023-06-01T13:54:57.057676image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum27
Range27
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0961556
Coefficient of variation (CV)2.7586194
Kurtosis109.619
Mean0.39735658
Median Absolute Deviation (MAD)0
Skewness6.8039367
Sum1413
Variance1.201557
MonotonicityNot monotonic
2023-06-01T13:54:57.167046image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 2873
80.8%
1 307
 
8.6%
2 207
 
5.8%
3 83
 
2.3%
4 53
 
1.5%
5 11
 
0.3%
6 10
 
0.3%
8 7
 
0.2%
7 3
 
0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
0 2873
80.8%
1 307
 
8.6%
2 207
 
5.8%
3 83
 
2.3%
4 53
 
1.5%
5 11
 
0.3%
6 10
 
0.3%
7 3
 
0.1%
8 7
 
0.2%
12 1
 
< 0.1%
ValueCountFrequency (%)
27 1
 
< 0.1%
12 1
 
< 0.1%
8 7
 
0.2%
7 3
 
0.1%
6 10
 
0.3%
5 11
 
0.3%
4 53
 
1.5%
3 83
 
2.3%
2 207
5.8%
1 307
8.6%

Total.Serious.Injuries
Real number (ℝ)

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1988189
Minimum0
Maximum10
Zeros3104
Zeros (%)87.3%
Negative0
Negative (%)0.0%
Memory size55.6 KiB
2023-06-01T13:54:57.279910image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.646626
Coefficient of variation (CV)3.2523367
Kurtosis45.766254
Mean0.1988189
Median Absolute Deviation (MAD)0
Skewness5.4052813
Sum707
Variance0.41812519
MonotonicityNot monotonic
2023-06-01T13:54:57.391074image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 3104
87.3%
1 296
 
8.3%
2 104
 
2.9%
3 29
 
0.8%
4 14
 
0.4%
5 4
 
0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 3104
87.3%
1 296
 
8.3%
2 104
 
2.9%
3 29
 
0.8%
4 14
 
0.4%
5 4
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 4
 
0.1%
4 14
 
0.4%
3 29
 
0.8%
2 104
 
2.9%
1 296
8.3%

Total.Minor.Injuries
Real number (ℝ)

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.27446569
Minimum0
Maximum33
Zeros2969
Zeros (%)83.5%
Negative0
Negative (%)0.0%
Memory size55.6 KiB
2023-06-01T13:54:57.504734image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum33
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0864362
Coefficient of variation (CV)3.9583679
Kurtosis399.43429
Mean0.27446569
Median Absolute Deviation (MAD)0
Skewness16.411596
Sum976
Variance1.1803436
MonotonicityNot monotonic
2023-06-01T13:54:57.608218image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 2969
83.5%
1 384
 
10.8%
2 143
 
4.0%
3 35
 
1.0%
4 15
 
0.4%
6 3
 
0.1%
5 2
 
0.1%
24 1
 
< 0.1%
25 1
 
< 0.1%
19 1
 
< 0.1%
Other values (2) 2
 
0.1%
ValueCountFrequency (%)
0 2969
83.5%
1 384
 
10.8%
2 143
 
4.0%
3 35
 
1.0%
4 15
 
0.4%
5 2
 
0.1%
6 3
 
0.1%
12 1
 
< 0.1%
19 1
 
< 0.1%
24 1
 
< 0.1%
ValueCountFrequency (%)
33 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
19 1
 
< 0.1%
12 1
 
< 0.1%
6 3
 
0.1%
5 2
 
0.1%
4 15
 
0.4%
3 35
 
1.0%
2 143
4.0%

Total.Uninjured
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct40
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9195726
Minimum0
Maximum393
Zeros1266
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size55.6 KiB
2023-06-01T13:54:57.747229image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum393
Range393
Interquartile range (IQR)2

Descriptive statistics

Standard deviation10.541099
Coefficient of variation (CV)5.4913782
Kurtosis627.27485
Mean1.9195726
Median Absolute Deviation (MAD)1
Skewness21.691115
Sum6826
Variance111.11477
MonotonicityNot monotonic
2023-06-01T13:54:57.898743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 1266
35.6%
1 1134
31.9%
2 660
18.6%
3 221
 
6.2%
4 154
 
4.3%
5 43
 
1.2%
6 20
 
0.6%
7 11
 
0.3%
8 6
 
0.2%
11 4
 
0.1%
Other values (30) 37
 
1.0%
ValueCountFrequency (%)
0 1266
35.6%
1 1134
31.9%
2 660
18.6%
3 221
 
6.2%
4 154
 
4.3%
5 43
 
1.2%
6 20
 
0.6%
7 11
 
0.3%
8 6
 
0.2%
9 3
 
0.1%
ValueCountFrequency (%)
393 1
< 0.1%
182 1
< 0.1%
154 1
< 0.1%
152 1
< 0.1%
142 1
< 0.1%
137 1
< 0.1%
136 1
< 0.1%
129 1
< 0.1%
119 1
< 0.1%
116 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
2514 
1
1042 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 2514
70.7%
1 1042
29.3%

Length

2023-06-01T13:54:58.042929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:58.162265image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2514
70.7%
1 1042
29.3%

Most occurring characters

ValueCountFrequency (%)
0 2514
70.7%
1 1042
29.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2514
70.7%
1 1042
29.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2514
70.7%
1 1042
29.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2514
70.7%
1 1042
29.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3433 
1
 
123

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3433
96.5%
1 123
 
3.5%

Length

2023-06-01T13:54:58.267507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:58.388536image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3433
96.5%
1 123
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 3433
96.5%
1 123
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3433
96.5%
1 123
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3433
96.5%
1 123
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3433
96.5%
1 123
 
3.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
1
2391 
0
1165 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 2391
67.2%
0 1165
32.8%

Length

2023-06-01T13:54:58.486973image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:58.611239image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2391
67.2%
0 1165
32.8%

Most occurring characters

ValueCountFrequency (%)
1 2391
67.2%
0 1165
32.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2391
67.2%
0 1165
32.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2391
67.2%
0 1165
32.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2391
67.2%
0 1165
32.8%

Amateur.Built_No
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
1
3321 
0
 
235

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 3321
93.4%
0 235
 
6.6%

Length

2023-06-01T13:54:58.716651image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:58.837283image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3321
93.4%
0 235
 
6.6%

Most occurring characters

ValueCountFrequency (%)
1 3321
93.4%
0 235
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3321
93.4%
0 235
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3321
93.4%
0 235
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3321
93.4%
0 235
 
6.6%

Amateur.Built_Yes
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3321 
1
 
235

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3321
93.4%
1 235
 
6.6%

Length

2023-06-01T13:54:58.935908image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:59.054068image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3321
93.4%
1 235
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0 3321
93.4%
1 235
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3321
93.4%
1 235
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3321
93.4%
1 235
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3321
93.4%
1 235
 
6.6%

Engine.Type_reciprocating
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
1
3217 
0
339 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 3217
90.5%
0 339
 
9.5%

Length

2023-06-01T13:54:59.155232image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:59.279658image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3217
90.5%
0 339
 
9.5%

Most occurring characters

ValueCountFrequency (%)
1 3217
90.5%
0 339
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3217
90.5%
0 339
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3217
90.5%
0 339
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3217
90.5%
0 339
 
9.5%

Engine.Type_turbo fan
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3530 
1
 
26

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3530
99.3%
1 26
 
0.7%

Length

2023-06-01T13:54:59.382932image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:59.503724image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3530
99.3%
1 26
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 3530
99.3%
1 26
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3530
99.3%
1 26
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3530
99.3%
1 26
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3530
99.3%
1 26
 
0.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3540 
1
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3540
99.6%
1 16
 
0.4%

Length

2023-06-01T13:54:59.606695image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:59.726806image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3540
99.6%
1 16
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 3540
99.6%
1 16
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3540
99.6%
1 16
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3540
99.6%
1 16
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3540
99.6%
1 16
 
0.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3476 
1
 
80

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3476
97.8%
1 80
 
2.2%

Length

2023-06-01T13:54:59.825517image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:54:59.946042image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3476
97.8%
1 80
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 3476
97.8%
1 80
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3476
97.8%
1 80
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3476
97.8%
1 80
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3476
97.8%
1 80
 
2.2%

Engine.Type_turbo shaft
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3412 
1
 
144

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3412
96.0%
1 144
 
4.0%

Length

2023-06-01T13:55:00.053543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:00.175518image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3412
96.0%
1 144
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 3412
96.0%
1 144
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3412
96.0%
1 144
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3412
96.0%
1 144
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3412
96.0%
1 144
 
4.0%

Engine.Type_unknown
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3483 
1
 
73

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3483
97.9%
1 73
 
2.1%

Length

2023-06-01T13:55:00.273603image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:00.392793image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3483
97.9%
1 73
 
2.1%

Most occurring characters

ValueCountFrequency (%)
0 3483
97.9%
1 73
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3483
97.9%
1 73
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3483
97.9%
1 73
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3483
97.9%
1 73
 
2.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3393 
1
 
163

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3393
95.4%
1 163
 
4.6%

Length

2023-06-01T13:55:00.495523image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:00.617512image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3393
95.4%
1 163
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 3393
95.4%
1 163
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3393
95.4%
1 163
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3393
95.4%
1 163
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3393
95.4%
1 163
 
4.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3543 
1
 
13

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3543
99.6%
1 13
 
0.4%

Length

2023-06-01T13:55:00.716925image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:00.837646image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3543
99.6%
1 13
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 3543
99.6%
1 13
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3543
99.6%
1 13
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3543
99.6%
1 13
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3543
99.6%
1 13
 
0.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3261 
1
 
295

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3261
91.7%
1 295
 
8.3%

Length

2023-06-01T13:55:00.939917image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:01.066028image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3261
91.7%
1 295
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 3261
91.7%
1 295
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3261
91.7%
1 295
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3261
91.7%
1 295
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3261
91.7%
1 295
 
8.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3507 
1
 
49

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3507
98.6%
1 49
 
1.4%

Length

2023-06-01T13:55:01.168184image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:01.573350image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3507
98.6%
1 49
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 3507
98.6%
1 49
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3507
98.6%
1 49
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3507
98.6%
1 49
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3507
98.6%
1 49
 
1.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3486 
1
 
70

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3486
98.0%
1 70
 
2.0%

Length

2023-06-01T13:55:01.671909image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:01.793316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3486
98.0%
1 70
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 3486
98.0%
1 70
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3486
98.0%
1 70
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3486
98.0%
1 70
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3486
98.0%
1 70
 
2.0%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3554 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Length

2023-06-01T13:55:01.895133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:02.015524image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3555 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Length

2023-06-01T13:55:02.113919image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:02.235138image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3141 
1
415 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3141
88.3%
1 415
 
11.7%

Length

2023-06-01T13:55:02.336689image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:02.457523image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3141
88.3%
1 415
 
11.7%

Most occurring characters

ValueCountFrequency (%)
0 3141
88.3%
1 415
 
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3141
88.3%
1 415
 
11.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3141
88.3%
1 415
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3141
88.3%
1 415
 
11.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3555 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Length

2023-06-01T13:55:02.558404image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:02.679790image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
1
1933 
0
1623 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1933
54.4%
0 1623
45.6%

Length

2023-06-01T13:55:02.781633image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:02.902482image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1933
54.4%
0 1623
45.6%

Most occurring characters

ValueCountFrequency (%)
1 1933
54.4%
0 1623
45.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1933
54.4%
0 1623
45.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1933
54.4%
0 1623
45.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1933
54.4%
0 1623
45.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3535 
1
 
21

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Length

2023-06-01T13:55:03.003955image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:03.125401image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3551 
1
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3551
99.9%
1 5
 
0.1%

Length

2023-06-01T13:55:03.227336image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:03.346436image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3551
99.9%
1 5
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 3551
99.9%
1 5
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3551
99.9%
1 5
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3551
99.9%
1 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3551
99.9%
1 5
 
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3555 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Length

2023-06-01T13:55:03.445309image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:03.567299image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3555 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Length

2023-06-01T13:55:03.670036image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:03.789231image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3555 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Length

2023-06-01T13:55:03.888207image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:04.011145image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
2971 
1
585 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2971
83.5%
1 585
 
16.5%

Length

2023-06-01T13:55:04.112324image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:04.235657image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2971
83.5%
1 585
 
16.5%

Most occurring characters

ValueCountFrequency (%)
0 2971
83.5%
1 585
 
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2971
83.5%
1 585
 
16.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2971
83.5%
1 585
 
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2971
83.5%
1 585
 
16.5%

Weather.Condition_IMC
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3231 
1
325 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 3231
90.9%
1 325
 
9.1%

Length

2023-06-01T13:55:04.337724image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:04.461697image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3231
90.9%
1 325
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 3231
90.9%
1 325
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3231
90.9%
1 325
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3231
90.9%
1 325
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3231
90.9%
1 325
 
9.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3502 
1
 
54

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Length

2023-06-01T13:55:04.566578image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:04.687738image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Weather.Condition_VMC
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
1
3177 
0
379 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 3177
89.3%
0 379
 
10.7%

Length

2023-06-01T13:55:04.786146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:04.910725image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3177
89.3%
0 379
 
10.7%

Most occurring characters

ValueCountFrequency (%)
1 3177
89.3%
0 379
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3177
89.3%
0 379
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3177
89.3%
0 379
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3177
89.3%
0 379
 
10.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3168 
1
388 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3168
89.1%
1 388
 
10.9%

Length

2023-06-01T13:55:05.016894image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:05.137835image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3168
89.1%
1 388
 
10.9%

Most occurring characters

ValueCountFrequency (%)
0 3168
89.1%
1 388
 
10.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3168
89.1%
1 388
 
10.9%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3168
89.1%
1 388
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3168
89.1%
1 388
 
10.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3464 
1
 
92

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3464
97.4%
1 92
 
2.6%

Length

2023-06-01T13:55:05.242101image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:05.363993image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3464
97.4%
1 92
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 3464
97.4%
1 92
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3464
97.4%
1 92
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3464
97.4%
1 92
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3464
97.4%
1 92
 
2.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
2947 
1
609 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 2947
82.9%
1 609
 
17.1%

Length

2023-06-01T13:55:05.465843image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:05.587644image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2947
82.9%
1 609
 
17.1%

Most occurring characters

ValueCountFrequency (%)
0 2947
82.9%
1 609
 
17.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2947
82.9%
1 609
 
17.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2947
82.9%
1 609
 
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2947
82.9%
1 609
 
17.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3461 
1
 
95

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Length

2023-06-01T13:55:05.690833image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:05.813809image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3499 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Length

2023-06-01T13:55:05.915180image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:06.033586image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
2632 
1
924 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2632
74.0%
1 924
 
26.0%

Length

2023-06-01T13:55:06.132824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:06.255188image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2632
74.0%
1 924
 
26.0%

Most occurring characters

ValueCountFrequency (%)
0 2632
74.0%
1 924
 
26.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2632
74.0%
1 924
 
26.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2632
74.0%
1 924
 
26.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2632
74.0%
1 924
 
26.0%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3126 
1
430 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3126
87.9%
1 430
 
12.1%

Length

2023-06-01T13:55:06.360222image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:06.479995image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3126
87.9%
1 430
 
12.1%

Most occurring characters

ValueCountFrequency (%)
0 3126
87.9%
1 430
 
12.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3126
87.9%
1 430
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3126
87.9%
1 430
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3126
87.9%
1 430
 
12.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3531 
1
 
25

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3531
99.3%
1 25
 
0.7%

Length

2023-06-01T13:55:06.583458image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:06.705221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3531
99.3%
1 25
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 3531
99.3%
1 25
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3531
99.3%
1 25
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3531
99.3%
1 25
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3531
99.3%
1 25
 
0.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
2804 
1
752 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 2804
78.9%
1 752
 
21.1%

Length

2023-06-01T13:55:06.806915image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:06.925624image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2804
78.9%
1 752
 
21.1%

Most occurring characters

ValueCountFrequency (%)
0 2804
78.9%
1 752
 
21.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2804
78.9%
1 752
 
21.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2804
78.9%
1 752
 
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2804
78.9%
1 752
 
21.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3430 
1
 
126

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Length

2023-06-01T13:55:07.028919image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:07.150538image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3498 
1
 
58

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Length

2023-06-01T13:55:07.252124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:07.369095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

States_AK
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3359 
1
 
197

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3359
94.5%
1 197
 
5.5%

Length

2023-06-01T13:55:07.469064image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:07.590185image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3359
94.5%
1 197
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 3359
94.5%
1 197
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3359
94.5%
1 197
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3359
94.5%
1 197
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3359
94.5%
1 197
 
5.5%

States_AL
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3497 
1
 
59

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3497
98.3%
1 59
 
1.7%

Length

2023-06-01T13:55:07.690591image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:07.809307image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3497
98.3%
1 59
 
1.7%

Most occurring characters

ValueCountFrequency (%)
0 3497
98.3%
1 59
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3497
98.3%
1 59
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3497
98.3%
1 59
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3497
98.3%
1 59
 
1.7%

States_AR
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3488 
1
 
68

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3488
98.1%
1 68
 
1.9%

Length

2023-06-01T13:55:07.908286image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:08.030835image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3488
98.1%
1 68
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0 3488
98.1%
1 68
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3488
98.1%
1 68
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3488
98.1%
1 68
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3488
98.1%
1 68
 
1.9%

States_AZ
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3430 
1
 
126

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Length

2023-06-01T13:55:08.493682image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:08.619023image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3430
96.5%
1 126
 
3.5%

States_CA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3153 
1
403 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3153
88.7%
1 403
 
11.3%

Length

2023-06-01T13:55:08.717697image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:08.839397image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3153
88.7%
1 403
 
11.3%

Most occurring characters

ValueCountFrequency (%)
0 3153
88.7%
1 403
 
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3153
88.7%
1 403
 
11.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3153
88.7%
1 403
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3153
88.7%
1 403
 
11.3%

States_CO
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3458 
1
 
98

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Length

2023-06-01T13:55:08.944764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:09.064770image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

States_CT
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3535 
1
 
21

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Length

2023-06-01T13:55:09.162852image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:09.283597image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3535
99.4%
1 21
 
0.6%

States_DC
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3554 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Length

2023-06-01T13:55:09.385677image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:09.510996image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3554
99.9%
1 2
 
0.1%

States_DE
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3552 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3552
99.9%
1 4
 
0.1%

Length

2023-06-01T13:55:09.609737image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:09.732472image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3552
99.9%
1 4
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 3552
99.9%
1 4
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3552
99.9%
1 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3552
99.9%
1 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3552
99.9%
1 4
 
0.1%

States_FL
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3357 
1
 
199

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3357
94.4%
1 199
 
5.6%

Length

2023-06-01T13:55:09.836135image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:09.958371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3357
94.4%
1 199
 
5.6%

Most occurring characters

ValueCountFrequency (%)
0 3357
94.4%
1 199
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3357
94.4%
1 199
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3357
94.4%
1 199
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3357
94.4%
1 199
 
5.6%

States_GA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3472 
1
 
84

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3472
97.6%
1 84
 
2.4%

Length

2023-06-01T13:55:10.059066image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:10.179798image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3472
97.6%
1 84
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 3472
97.6%
1 84
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3472
97.6%
1 84
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3472
97.6%
1 84
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3472
97.6%
1 84
 
2.4%

States_HI
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3544 
1
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3544
99.7%
1 12
 
0.3%

Length

2023-06-01T13:55:10.282793image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:10.417867image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3544
99.7%
1 12
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 3544
99.7%
1 12
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3544
99.7%
1 12
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3544
99.7%
1 12
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3544
99.7%
1 12
 
0.3%

States_IA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3503 
1
 
53

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3503
98.5%
1 53
 
1.5%

Length

2023-06-01T13:55:10.523546image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:10.655334image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3503
98.5%
1 53
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0 3503
98.5%
1 53
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3503
98.5%
1 53
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3503
98.5%
1 53
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3503
98.5%
1 53
 
1.5%

States_ID
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3509 
1
 
47

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Length

2023-06-01T13:55:10.761505image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:10.884769image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

States_IL
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3458 
1
 
98

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Length

2023-06-01T13:55:10.989676image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:11.123792image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3458
97.2%
1 98
 
2.8%

States_IN
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3501 
1
 
55

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3501
98.5%
1 55
 
1.5%

Length

2023-06-01T13:55:11.232395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:11.360505image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3501
98.5%
1 55
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0 3501
98.5%
1 55
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3501
98.5%
1 55
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3501
98.5%
1 55
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3501
98.5%
1 55
 
1.5%

States_KS
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3499 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Length

2023-06-01T13:55:11.466777image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:11.600248image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3499
98.4%
1 57
 
1.6%

States_KY
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3515 
1
 
41

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Length

2023-06-01T13:55:11.708774image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:11.830541image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

States_LA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3479 
1
 
77

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3479
97.8%
1 77
 
2.2%

Length

2023-06-01T13:55:11.932102image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:12.059299image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3479
97.8%
1 77
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 3479
97.8%
1 77
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3479
97.8%
1 77
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3479
97.8%
1 77
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3479
97.8%
1 77
 
2.2%

States_MA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3520 
1
 
36

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Length

2023-06-01T13:55:12.169372image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:12.293263image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

States_MD
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3529 
1
 
27

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3529
99.2%
1 27
 
0.8%

Length

2023-06-01T13:55:12.400533image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:12.529843image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3529
99.2%
1 27
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 3529
99.2%
1 27
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3529
99.2%
1 27
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3529
99.2%
1 27
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3529
99.2%
1 27
 
0.8%

States_ME
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3537 
1
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Length

2023-06-01T13:55:12.633379image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:12.751935image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

States_MI
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3471 
1
 
85

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Length

2023-06-01T13:55:12.853863image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:12.973279image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

States_MN
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3494 
1
 
62

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3494
98.3%
1 62
 
1.7%

Length

2023-06-01T13:55:13.074055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:13.192227image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3494
98.3%
1 62
 
1.7%

Most occurring characters

ValueCountFrequency (%)
0 3494
98.3%
1 62
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3494
98.3%
1 62
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3494
98.3%
1 62
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3494
98.3%
1 62
 
1.7%

States_MO
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3469 
1
 
87

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3469
97.6%
1 87
 
2.4%

Length

2023-06-01T13:55:13.294221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:13.416837image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3469
97.6%
1 87
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 3469
97.6%
1 87
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3469
97.6%
1 87
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3469
97.6%
1 87
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3469
97.6%
1 87
 
2.4%

States_MS
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3520 
1
 
36

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Length

2023-06-01T13:55:13.518063image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:13.638817image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3520
99.0%
1 36
 
1.0%

States_MT
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3498 
1
 
58

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Length

2023-06-01T13:55:13.741073image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:13.862539image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3498
98.4%
1 58
 
1.6%

States_NC
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3492 
1
 
64

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Length

2023-06-01T13:55:13.963716image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:14.081379image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring characters

ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

States_ND
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3526 
1
 
30

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3526
99.2%
1 30
 
0.8%

Length

2023-06-01T13:55:14.183517image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:14.303728image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3526
99.2%
1 30
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 3526
99.2%
1 30
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3526
99.2%
1 30
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3526
99.2%
1 30
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3526
99.2%
1 30
 
0.8%

States_NE
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3515 
1
 
41

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Length

2023-06-01T13:55:14.406404image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:14.524288image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

States_NH
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3537 
1
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Length

2023-06-01T13:55:14.627793image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:14.750135image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3537
99.5%
1 19
 
0.5%

States_NJ
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3509 
1
 
47

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Length

2023-06-01T13:55:14.851453image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:14.968615image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3509
98.7%
1 47
 
1.3%

States_NM
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3490 
1
 
66

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3490
98.1%
1 66
 
1.9%

Length

2023-06-01T13:55:15.071331image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:15.191788image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3490
98.1%
1 66
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0 3490
98.1%
1 66
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3490
98.1%
1 66
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3490
98.1%
1 66
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3490
98.1%
1 66
 
1.9%

States_NV
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3514 
1
 
42

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3514
98.8%
1 42
 
1.2%

Length

2023-06-01T13:55:15.292297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:15.412338image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3514
98.8%
1 42
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 3514
98.8%
1 42
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3514
98.8%
1 42
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3514
98.8%
1 42
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3514
98.8%
1 42
 
1.2%

States_NY
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3465 
1
 
91

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3465
97.4%
1 91
 
2.6%

Length

2023-06-01T13:55:15.515978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:15.635828image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3465
97.4%
1 91
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 3465
97.4%
1 91
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3465
97.4%
1 91
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3465
97.4%
1 91
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3465
97.4%
1 91
 
2.6%

States_OH
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3474 
1
 
82

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3474
97.7%
1 82
 
2.3%

Length

2023-06-01T13:55:15.735834image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:15.853947image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3474
97.7%
1 82
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 3474
97.7%
1 82
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3474
97.7%
1 82
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3474
97.7%
1 82
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3474
97.7%
1 82
 
2.3%

States_OK
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3492 
1
 
64

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Length

2023-06-01T13:55:15.955877image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:16.077090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring characters

ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3492
98.2%
1 64
 
1.8%

States_OR
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3471 
1
 
85

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Length

2023-06-01T13:55:16.177585image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:16.294984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3471
97.6%
1 85
 
2.4%

States_PA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3459 
1
 
97

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3459
97.3%
1 97
 
2.7%

Length

2023-06-01T13:55:16.401212image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:16.520874image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3459
97.3%
1 97
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 3459
97.3%
1 97
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3459
97.3%
1 97
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3459
97.3%
1 97
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3459
97.3%
1 97
 
2.7%

States_PR
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3555 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Length

2023-06-01T13:55:16.621311image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:17.200622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3555
> 99.9%
1 1
 
< 0.1%

States_RI
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3550 
1
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3550
99.8%
1 6
 
0.2%

Length

2023-06-01T13:55:17.303477image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:17.425163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3550
99.8%
1 6
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 3550
99.8%
1 6
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3550
99.8%
1 6
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3550
99.8%
1 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3550
99.8%
1 6
 
0.2%

States_SC
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3505 
1
 
51

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3505
98.6%
1 51
 
1.4%

Length

2023-06-01T13:55:17.526863image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:17.644258image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3505
98.6%
1 51
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 3505
98.6%
1 51
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3505
98.6%
1 51
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3505
98.6%
1 51
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3505
98.6%
1 51
 
1.4%

States_SD
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3538 
1
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3538
99.5%
1 18
 
0.5%

Length

2023-06-01T13:55:17.747514image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:17.868144image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3538
99.5%
1 18
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 3538
99.5%
1 18
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3538
99.5%
1 18
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3538
99.5%
1 18
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3538
99.5%
1 18
 
0.5%

States_TN
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3523 
1
 
33

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3523
99.1%
1 33
 
0.9%

Length

2023-06-01T13:55:17.971794image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:18.088954image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3523
99.1%
1 33
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 3523
99.1%
1 33
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3523
99.1%
1 33
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3523
99.1%
1 33
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3523
99.1%
1 33
 
0.9%

States_TX
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3254 
1
 
302

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 3254
91.5%
1 302
 
8.5%

Length

2023-06-01T13:55:18.193180image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:18.314557image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3254
91.5%
1 302
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 3254
91.5%
1 302
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3254
91.5%
1 302
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3254
91.5%
1 302
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3254
91.5%
1 302
 
8.5%

States_UT
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3512 
1
 
44

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3512
98.8%
1 44
 
1.2%

Length

2023-06-01T13:55:18.420050image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:18.536728image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3512
98.8%
1 44
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 3512
98.8%
1 44
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3512
98.8%
1 44
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3512
98.8%
1 44
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3512
98.8%
1 44
 
1.2%

States_VA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3515 
1
 
41

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Length

2023-06-01T13:55:18.640575image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:18.761910image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3515
98.8%
1 41
 
1.2%

States_VT
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3546 
1
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3546
99.7%
1 10
 
0.3%

Length

2023-06-01T13:55:18.865018image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:18.981622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3546
99.7%
1 10
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 3546
99.7%
1 10
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3546
99.7%
1 10
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3546
99.7%
1 10
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3546
99.7%
1 10
 
0.3%

States_WA
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3461 
1
 
95

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Length

2023-06-01T13:55:19.084094image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:19.204903image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3461
97.3%
1 95
 
2.7%

States_WI
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3502 
1
 
54

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Length

2023-06-01T13:55:19.306189image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:19.424750image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3502
98.5%
1 54
 
1.5%

States_WV
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3539 
1
 
17

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3539
99.5%
1 17
 
0.5%

Length

2023-06-01T13:55:19.526514image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:19.649064image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3539
99.5%
1 17
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 3539
99.5%
1 17
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3539
99.5%
1 17
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3539
99.5%
1 17
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3539
99.5%
1 17
 
0.5%

States_WY
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
0
3511 
1
 
45

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3556
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3511
98.7%
1 45
 
1.3%

Length

2023-06-01T13:55:19.751745image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-01T13:55:19.869172image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3511
98.7%
1 45
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0 3511
98.7%
1 45
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3556
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3511
98.7%
1 45
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3511
98.7%
1 45
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3511
98.7%
1 45
 
1.3%

Interactions

2023-06-01T13:54:52.931754image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:51.297966image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:51.852289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:52.385564image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:53.069455image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:51.436223image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:51.983335image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:52.522886image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:53.203545image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:51.569782image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:52.112653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:52.654755image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:53.347384image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:51.711131image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:52.245347image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-06-01T13:54:52.788281image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2023-06-01T13:55:20.118891image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Total.Fatal.InjuriesTotal.Serious.InjuriesTotal.Minor.InjuriesTotal.UninjuredNumber.of.EnginesAircraft.damage_DestroyedAircraft.damage_MinorAircraft.damage_SubstantialAmateur.Built_NoAmateur.Built_YesEngine.Type_reciprocatingEngine.Type_turbo fanEngine.Type_turbo jetEngine.Type_turbo propEngine.Type_turbo shaftEngine.Type_unknownPurpose.of.flight_Aerial ApplicationPurpose.of.flight_Aerial ObservationPurpose.of.flight_BusinessPurpose.of.flight_Executive/corporatePurpose.of.flight_FerryPurpose.of.flight_Flight TestPurpose.of.flight_Glider TowPurpose.of.flight_InstructionalPurpose.of.flight_Other Work UsePurpose.of.flight_PersonalPurpose.of.flight_PositioningPurpose.of.flight_Public AircraftPurpose.of.flight_Public Aircraft - FederalPurpose.of.flight_Public Aircraft - LocalPurpose.of.flight_SkydivingPurpose.of.flight_UnknownWeather.Condition_IMCWeather.Condition_UNKWeather.Condition_VMCBroad.phase.of.flight_ApproachBroad.phase.of.flight_ClimbBroad.phase.of.flight_CruiseBroad.phase.of.flight_DescentBroad.phase.of.flight_Go-aroundBroad.phase.of.flight_LandingBroad.phase.of.flight_ManeuveringBroad.phase.of.flight_StandingBroad.phase.of.flight_TakeoffBroad.phase.of.flight_TaxiBroad.phase.of.flight_UnknownStates_AKStates_ALStates_ARStates_AZStates_CAStates_COStates_CTStates_DCStates_DEStates_FLStates_GAStates_HIStates_IAStates_IDStates_ILStates_INStates_KSStates_KYStates_LAStates_MAStates_MDStates_MEStates_MIStates_MNStates_MOStates_MSStates_MTStates_NCStates_NDStates_NEStates_NHStates_NJStates_NMStates_NVStates_NYStates_OHStates_OKStates_ORStates_PAStates_PRStates_RIStates_SCStates_SDStates_TNStates_TXStates_UTStates_VAStates_VTStates_WAStates_WIStates_WVStates_WY
Total.Fatal.Injuries1.0000.029-0.148-0.5380.0630.3160.0260.2900.0000.0000.0680.1930.0390.0860.0730.0000.0360.0000.0360.0040.0000.0000.0000.0600.0730.0330.0890.0000.0000.0000.0000.0330.1770.0830.1850.0000.0560.1440.0000.0250.1220.0000.0000.0560.0270.0540.0000.0000.0000.0360.0610.0000.0000.0000.0000.0150.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0340.0000.0990.0000.0000.0000.0000.0000.0000.0000.0000.0000.0550.0420.0560.0000.0180.0000.0000.000
Total.Serious.Injuries0.0291.0000.088-0.3660.1380.1520.0800.1360.0000.0000.1060.2760.0000.1580.0000.0260.0000.0410.0000.0000.0000.0000.0000.0000.0000.0450.0000.1060.0000.0000.0830.1030.0330.0000.0290.0570.1020.0370.0370.0310.0570.0000.0000.0130.0000.0000.0890.0000.0000.0000.0000.0000.0950.0000.0000.0000.0000.0580.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0380.0000.0000.0000.0000.0000.0000.0000.0940.0180.0000.0000.0000.0000.4050.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.159
Total.Minor.Injuries-0.1480.0881.000-0.2890.2300.0000.1210.0290.0000.0000.1090.4360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0780.0750.0000.0690.0340.0000.0150.0000.0000.0000.0000.0100.0190.0490.0330.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1100.0000.0000.0000.0000.0000.0000.0000.0000.0000.1530.0000.0000.0000.0000.0970.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.144
Total.Uninjured-0.538-0.366-0.2891.0000.3810.0340.2400.0450.0000.0000.2100.7200.1830.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0660.0000.0000.0000.0000.0000.1520.0700.0000.0610.0000.0000.0000.0000.0640.0000.0000.0620.0340.0000.0000.0000.0000.0000.0000.0000.0340.0000.0000.0000.0350.0000.2860.0000.0490.0000.0000.0000.0000.0000.1620.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.0000.0910.0510.0000.0000.0000.0000.0000.0000.036
Number.of.Engines0.0630.1380.2300.3811.0000.0310.2900.1120.0680.0680.5480.7420.2410.3280.0320.9930.0910.0000.1660.2270.0920.0000.0000.0910.0000.2350.1470.0380.0000.0000.0000.2100.1820.0410.1720.0730.0100.0370.0000.0010.0180.0910.0410.0000.0320.0000.0430.0000.0170.0630.0210.0210.0000.0490.0000.0570.0000.0740.0000.0000.0000.0570.0000.0000.0000.0340.0000.0000.0270.0000.0000.0000.0000.0210.0000.0000.0680.0000.0450.0000.0280.0000.0000.0230.0000.0260.0000.0440.0000.0270.0380.0000.0000.0000.0490.0000.0000.028
Aircraft.damage_Destroyed0.3160.1520.0000.0340.0311.0000.1190.9220.0850.0850.0000.0250.0000.0240.0420.0020.0500.0340.0210.0260.0150.0000.0000.0970.0000.0220.0000.0000.0000.0000.0000.0000.2250.0460.2310.0000.0580.1200.0140.0000.2650.1970.0120.0000.0970.0840.0600.0000.0190.0000.1030.0160.0000.0000.0000.0000.0000.0390.0260.0110.0260.0000.0000.0000.0240.0000.0000.0000.0060.0040.0360.0390.0000.0000.0390.0000.0000.0000.0000.0310.0400.0000.0050.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.000
Aircraft.damage_Minor0.0260.0800.1210.2400.2900.1191.0000.2690.0230.0230.2240.2810.0660.2040.0000.0130.0160.0000.0000.1020.0000.0000.0000.0160.0000.1020.0000.0000.0000.0000.0000.1450.0230.0000.0140.0000.0000.0000.0000.0000.0290.0410.1400.0000.0830.0000.0000.0240.0000.0270.0000.0000.0000.0910.0000.0000.0540.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0100.0410.0000.0070.0470.0000.0000.0000.0000.0110.0000.0160.0000.0000.0000.0050.0000.0000.0000.0000.0140.0000.0000.0000.0000.0030.0000.0120.000
Aircraft.damage_Substantial0.2900.1360.0290.0450.1120.9220.2691.0000.0690.0690.0810.0750.0110.0470.0430.0000.0370.0270.0130.0000.0000.0000.0000.1040.0000.0000.0000.0000.0000.0000.0000.0590.2300.0400.2330.0000.0630.1130.0170.0000.2700.1730.0260.0000.0590.0760.0530.0000.0080.0000.0920.0120.0080.0130.0130.0000.0220.0440.0300.0130.0270.0030.0000.0000.0200.0100.0000.0000.0000.0210.0100.0300.0000.0120.0310.0000.0080.0000.0150.0270.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.000
Amateur.Built_No0.0000.0000.0000.0000.0680.0850.0230.0691.0000.9980.0250.0000.0000.0000.0300.0130.0530.0000.0420.0000.0000.0050.0000.0460.0000.1070.0000.0000.0000.0000.0000.0180.0480.0000.0470.0050.0000.0160.0290.0000.0310.0530.0000.0140.0040.0000.0540.0000.0000.0000.0390.0000.0000.0000.0740.0220.0150.0000.0000.0000.0300.0000.0000.0090.0110.0000.0000.0000.0000.0000.0310.0000.0000.0000.0070.0000.0000.0000.0000.0000.0190.0430.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0370.0000.0240.0320.0000.019
Amateur.Built_Yes0.0000.0000.0000.0000.0680.0850.0230.0690.9981.0000.0250.0000.0000.0000.0300.0130.0530.0000.0420.0000.0000.0050.0000.0460.0000.1070.0000.0000.0000.0000.0000.0180.0480.0000.0470.0050.0000.0160.0290.0000.0310.0530.0000.0140.0040.0000.0540.0000.0000.0000.0390.0000.0000.0000.0740.0220.0150.0000.0000.0000.0300.0000.0000.0090.0110.0000.0000.0000.0000.0000.0310.0000.0000.0000.0070.0000.0000.0000.0000.0000.0190.0430.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0370.0000.0240.0320.0000.019
Engine.Type_reciprocating0.0680.1060.1090.2100.5480.0000.2240.0810.0250.0251.0000.2580.1990.4640.6300.4420.0160.0000.0000.1040.0200.0000.0000.0820.0160.1830.1930.0200.0160.0160.0000.2290.0230.0000.0160.0020.0000.0130.0000.0250.0240.0360.0680.0230.0000.0000.0140.0000.0220.0000.0000.0510.0000.0000.0000.0150.0000.0150.0000.0020.0300.0050.0000.0000.0000.0000.0160.0000.0000.0000.0000.0220.0000.0040.0000.0140.0000.0000.0000.0000.0030.0000.0290.0000.0000.0000.0140.0000.0000.0000.0290.0000.0000.0000.0130.0230.0000.041
Engine.Type_turbo fan0.1930.2760.4360.7200.7420.0250.2810.0750.0000.0000.2581.0000.0000.0000.0000.0000.0000.0000.0000.0870.0000.0000.0000.0200.0000.0890.0000.0000.0000.0000.0000.1350.0680.0000.0590.0000.0000.0030.0000.0000.0000.0210.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Engine.Type_turbo jet0.0390.0000.0000.1830.2410.0000.0660.0110.0000.0000.1990.0001.0000.0000.0000.0000.0000.0000.0060.0800.0000.0000.0000.0060.0000.0410.0000.0000.0000.0000.0000.0280.0000.0000.0180.0330.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0340.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.000
Engine.Type_turbo prop0.0860.1580.0000.0000.3280.0240.2040.0470.0000.0000.4640.0000.0001.0000.0200.0000.0000.0000.0290.1030.0360.0000.0000.0430.0000.1280.0000.0000.0000.0000.0000.1440.0370.0000.0330.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0170.0000.0340.0190.0320.0160.0180.0110.0000.0000.0000.0000.0300.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0020.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.000
Engine.Type_turbo shaft0.0730.0000.0000.0000.0320.0420.0000.0430.0300.0300.6300.0000.0000.0201.0000.0180.0000.0000.0000.0000.0030.0000.0000.0470.0350.1730.3100.0460.0350.0350.0000.1720.0000.0000.0000.0000.0000.0850.0000.0120.0660.0910.0570.0570.0110.0000.0000.0000.0160.0080.0000.0140.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0120.0180.0400.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0440.0000.0000.0000.0000.0000.0040.0000.0150.0000.0000.0000.0100.0000.057
Engine.Type_unknown0.0000.0260.0000.0000.9930.0020.0130.0000.0130.0130.4420.0000.0000.0000.0181.0000.0050.0000.0360.0000.0000.0000.0000.0080.0000.0730.0000.0000.0000.0000.0000.0080.0390.0000.0370.0000.0110.0330.0000.0000.0240.0000.0000.0000.0150.0000.0260.0000.0000.0000.0110.0070.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0550.0000.0430.0000.0000.0000.0000.0000.0070.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Aerial Application0.0360.0000.0000.0000.0910.0500.0160.0370.0530.0530.0160.0000.0000.0000.0000.0051.0000.0000.0610.0110.0200.0000.0000.0760.0000.2370.0000.0000.0000.0000.0000.0940.0650.0000.0580.0640.0160.0860.0270.0150.0990.4320.0000.0360.0260.0160.0470.0000.1300.0000.0130.0180.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0620.0000.0000.0000.0130.0340.0140.1040.0100.0000.0260.0420.0000.0000.0000.0060.0260.0110.0000.0000.0180.0000.0000.0000.0000.0000.0000.0080.0050.0000.0060.0000.0000.008
Purpose.of.flight_Aerial Observation0.0000.0410.0000.0000.0000.0340.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0590.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0230.0000.0000.0260.0680.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0590.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.053
Purpose.of.flight_Business0.0360.0000.0000.0000.1660.0210.0000.0130.0420.0420.0000.0000.0060.0290.0000.0360.0610.0001.0000.0260.0350.0000.0000.1060.0000.3270.0000.0000.0000.0000.0000.1310.0740.0000.0680.0140.0260.0370.0520.0000.0000.0640.0050.0000.0290.0080.0160.0120.0000.0000.0190.0210.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0540.0000.0120.0000.0030.0120.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0350.0240.0180.0000.0000.0000.0000.0100.0000.0000.0000.0200.0000.0000.0000.0000.0000.000
Purpose.of.flight_Executive/corporate0.0040.0000.0000.0000.2270.0260.1020.0000.0000.0000.1040.0870.0800.1030.0000.0000.0110.0000.0261.0000.0000.0000.0000.0350.0000.1250.0000.0000.0000.0000.0000.0460.0560.0000.0460.0000.0000.0000.0000.0000.0120.0190.0000.0000.0160.0000.0160.0000.0000.0000.0000.0000.0000.0000.0270.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Ferry0.0000.0000.0000.0000.0920.0150.0000.0000.0000.0000.0200.0000.0000.0360.0030.0000.0200.0000.0350.0001.0000.0000.0000.0450.0000.1520.0000.0000.0000.0000.0000.0580.0000.0000.0000.0120.0000.0480.0000.0000.0000.0330.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0060.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0070.0000.0300.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.000
Purpose.of.flight_Flight Test0.0000.0000.0000.0000.0000.0000.0000.0000.0050.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0000.0000.0000.0000.0500.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Glider Tow0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0460.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Instructional0.0600.0000.0000.0000.0910.0970.0160.1040.0460.0460.0820.0200.0060.0430.0470.0080.0760.0000.1060.0350.0450.0000.0001.0000.0000.3960.0150.0000.0000.0000.0000.1590.0970.0000.0940.0160.0240.0930.0000.0000.1400.0470.0000.0110.0000.0150.0530.0000.0140.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0210.0000.0000.0000.0120.0000.0500.0280.0320.0000.0000.0000.0000.0000.0000.0220.0130.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0160.0000.014
Purpose.of.flight_Other Work Use0.0730.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0350.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0610.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Personal0.0330.0450.0180.0660.2350.0220.1020.0000.1070.1070.1830.0890.0410.1280.1730.0730.2370.0590.3270.1250.1520.0000.0000.3960.0001.0000.0790.0290.0000.0000.0000.4830.0090.0000.0000.0040.0100.0470.0000.0000.0160.1290.0380.0000.0000.0140.0000.0180.0530.0000.0260.0000.0000.0000.0000.0000.0000.0100.0000.0000.0270.0000.0000.0000.0690.0000.0340.0000.0210.0000.0130.0000.0000.0000.0390.0190.0010.0000.0000.0240.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0030.0280.0000.0090.0080.019
Purpose.of.flight_Positioning0.0890.0000.0000.0000.1470.0000.0000.0000.0000.0000.1930.0000.0000.0000.3100.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0791.0000.0000.0000.0000.0000.0240.0110.0000.0000.0000.0000.0080.0000.0000.0000.0290.0000.0050.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0400.0000.0000.0000.0000.0170.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Public Aircraft0.0000.1060.0000.0000.0380.0000.0000.0000.0000.0000.0200.0000.0000.0000.0460.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0290.0001.0000.0000.0000.0000.0000.0210.0000.0160.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Public Aircraft - Federal0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0350.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Public Aircraft - Local0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0350.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0510.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Skydiving0.0000.0830.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0580.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Purpose.of.flight_Unknown0.0330.1030.0780.1520.2100.0000.1450.0590.0180.0180.2290.1350.0280.1440.1720.0080.0940.0120.1310.0460.0580.0000.0000.1590.0000.4830.0240.0000.0000.0000.0001.0000.0000.0370.0220.0000.0000.0000.0100.0000.0860.0150.0560.0430.0000.0170.0610.0000.0170.0000.0200.0110.0000.0000.0000.0000.0000.0280.0000.0420.0010.0000.0160.0000.0310.0000.0190.0000.0210.0000.0170.0070.0000.0000.0240.0000.0000.0000.0000.0000.0210.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.059
Weather.Condition_IMC0.1770.0330.0750.0700.1820.2250.0230.2300.0480.0480.0230.0680.0000.0370.0000.0390.0650.0000.0740.0560.0000.0000.0000.0970.0000.0090.0110.0210.0000.0000.0000.0001.0000.0310.9170.0670.0190.1880.0310.0460.1100.0630.0120.0800.0200.0000.0320.0000.0000.0200.0000.0000.0000.0000.0000.0230.0260.0000.0000.0000.0000.0000.0130.0400.0000.0050.0300.0000.0000.0000.0150.0000.0000.0000.0000.0000.0330.0000.0190.0000.0200.0000.0000.0220.0360.0170.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.000
Weather.Condition_UNK0.0830.0000.0000.0000.0410.0460.0000.0400.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0370.0311.0000.3550.0000.0000.0600.0000.0000.0170.0000.0000.0470.0000.0640.0000.0000.0000.0270.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0420.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Weather.Condition_VMC0.1850.0290.0690.0610.1720.2310.0140.2330.0470.0470.0160.0590.0180.0330.0000.0370.0580.0000.0680.0460.0000.0000.0000.0940.0000.0000.0000.0160.0000.0000.0000.0220.9170.3551.0000.0630.0130.2020.0320.0360.1130.0570.0000.0960.0240.0340.0250.0000.0000.0000.0180.0000.0000.0000.0000.0150.0290.0000.0000.0000.0000.0000.0000.0310.0000.0000.0220.0000.0000.0000.0000.0180.0000.0000.0020.0000.0260.0000.0030.0000.0140.0000.0000.0000.0360.0130.0000.0000.0000.0000.0000.0000.0070.0000.0120.0000.0000.000
Broad.phase.of.flight_Approach0.0000.0570.0340.0000.0730.0000.0000.0000.0050.0050.0020.0000.0330.0000.0000.0000.0640.0000.0140.0000.0120.0000.0000.0160.0000.0040.0000.0000.0000.0000.0000.0000.0670.0000.0631.0000.0520.1570.0530.0380.2060.1270.0170.1790.0620.0380.0000.0000.0280.0070.0130.0000.0000.0000.0000.0180.0000.0000.0000.0000.0160.0000.0000.0000.0250.0000.0000.0250.0000.0000.0310.0140.0000.0170.0050.0000.0000.0080.0070.0000.0400.0130.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0030.0000.0000.0090.0000.010
Broad.phase.of.flight_Climb0.0560.1020.0000.0000.0100.0580.0000.0630.0000.0000.0000.0000.0000.0000.0000.0110.0160.0000.0260.0000.0000.0000.0000.0240.0000.0100.0000.0000.0000.0000.0000.0000.0190.0000.0130.0521.0000.0700.0130.0000.0930.0550.0000.0810.0200.0000.0110.0000.0000.0000.0480.0130.0000.0000.0000.0000.0100.0000.0000.0000.0140.0000.0000.0000.0070.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0360.0170.0090.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Broad.phase.of.flight_Cruise0.1440.0370.0150.0000.0370.1200.0000.1130.0160.0160.0130.0030.0000.0000.0850.0330.0860.0230.0370.0000.0480.0000.0000.0930.0000.0470.0080.0000.0000.0000.0000.0000.1880.0600.2020.1570.0701.0000.0710.0520.2680.1670.0290.2340.0830.0530.0000.0000.0220.0000.0000.0000.0120.0000.0000.0260.0360.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0230.0000.0000.0110.0090.0000.0420.0000.0000.0000.0000.0000.0340.0190.0000.0000.0220.008
Broad.phase.of.flight_Descent0.0000.0370.0000.0000.0000.0140.0000.0170.0290.0290.0000.0000.0000.0000.0000.0000.0270.0000.0520.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0310.0000.0320.0530.0130.0711.0000.0000.0950.0560.0000.0820.0210.0000.0000.0000.0000.0000.0000.0000.0000.0280.0000.0000.0330.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0110.0000.0460.0000.0000.0000.0000.0000.0000.0000.0000.0270.0000.0000.000
Broad.phase.of.flight_Go-around0.0250.0310.0000.0640.0010.0000.0000.0000.0000.0000.0250.0000.0000.0000.0120.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0460.0000.0360.0380.0000.0520.0001.0000.0710.0410.0000.0610.0080.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.000
Broad.phase.of.flight_Landing0.1220.0570.0000.0000.0180.2650.0290.2700.0310.0310.0240.0000.0000.0000.0660.0240.0990.0260.0000.0120.0000.0000.0000.1400.0000.0160.0000.0000.0000.0000.0000.0860.1100.0170.1130.2060.0930.2680.0950.0711.0000.2180.0430.3060.1110.0720.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0440.0000.0000.0030.0110.0110.0070.0250.0000.0130.0000.0410.0150.0180.0000.0000.0000.0310.0120.0000.0000.0060.0160.0000.0000.0000.0000.0050.0000.0000.0000.0000.0090.0000.0000.0080.0000.000
Broad.phase.of.flight_Maneuvering0.0000.0000.0000.0000.0910.1970.0410.1730.0530.0530.0360.0210.0000.0000.0910.0000.4320.0680.0640.0190.0330.0000.0000.0470.0100.1290.0290.0000.0100.0000.0100.0150.0630.0000.0570.1270.0550.1670.0560.0410.2181.0000.0200.1900.0670.0410.0170.0000.0630.0000.0000.0060.0160.0000.0200.0230.0000.0000.0000.0130.0230.0000.0000.0110.0390.0000.0050.0000.0000.0110.0290.0770.0330.0130.0210.0000.0000.0000.0000.0000.0250.0000.0060.0000.0000.0000.0000.0000.0230.0000.0000.0280.0000.0000.0000.0000.0100.000
Broad.phase.of.flight_Standing0.0000.0000.0100.0620.0410.0120.1400.0260.0000.0000.0680.0000.0000.0130.0570.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0380.0000.0000.0000.0000.0000.0560.0120.0000.0000.0170.0000.0290.0000.0000.0430.0201.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0360.0000.0000.0110.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.000
Broad.phase.of.flight_Takeoff0.0560.0130.0190.0340.0000.0000.0000.0000.0140.0140.0230.0280.0100.0000.0570.0000.0360.0190.0000.0000.0000.0000.0000.0110.0000.0000.0050.0000.0000.0000.0000.0430.0800.0470.0960.1790.0810.2340.0820.0610.3060.1900.0361.0000.0960.0620.0730.0000.0120.0160.0320.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0180.0090.0000.0000.0120.0000.0000.0000.0160.0210.0070.0370.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0210.0130.0000.0040.0000.000
Broad.phase.of.flight_Taxi0.0270.0000.0490.0000.0320.0970.0830.0590.0040.0040.0000.0000.0000.0000.0110.0150.0260.0000.0290.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0240.0620.0200.0830.0210.0080.1110.0670.0000.0961.0000.0080.0000.0000.0130.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0290.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0090.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0050.0000.000
Broad.phase.of.flight_Unknown0.0540.0000.0330.0000.0000.0840.0000.0760.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0080.0000.0000.0000.0000.0150.0000.0140.0000.0000.0000.0000.0000.0170.0000.0640.0340.0380.0000.0530.0000.0000.0720.0410.0000.0620.0081.0000.0000.0000.0000.0000.0670.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0450.0000.000
States_AK0.0000.0890.0000.0000.0430.0600.0000.0530.0540.0540.0140.0000.0000.0000.0000.0260.0470.0000.0160.0160.0000.0000.0000.0530.0000.0000.0000.0360.0000.0000.0000.0610.0320.0000.0250.0000.0110.0000.0000.0200.0180.0170.0000.0730.0000.0001.0000.0210.0240.0400.0830.0330.0000.0000.0000.0540.0290.0000.0180.0150.0330.0190.0200.0120.0270.0070.0000.0000.0290.0220.0300.0070.0200.0230.0000.0120.0000.0150.0230.0120.0310.0290.0230.0290.0330.0000.0000.0170.0000.0030.0700.0140.0120.0000.0320.0190.0000.014
States_AL0.0000.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0610.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0211.0000.0000.0090.0400.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.000
States_AR0.0000.0000.0000.0000.0170.0190.0000.0080.0000.0000.0220.0000.0000.0000.0160.0000.1300.0000.0000.0000.0000.0000.0000.0140.0000.0530.0000.0000.0000.0000.0000.0170.0000.0000.0000.0280.0000.0220.0000.0000.0000.0630.0000.0120.0130.0000.0240.0001.0000.0130.0440.0040.0000.0000.0000.0240.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0350.0000.0000.0000.0000.0000.0000.000
States_AZ0.0360.0000.0000.0000.0630.0000.0270.0000.0000.0000.0000.0000.0130.0170.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0270.0000.0070.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0400.0090.0131.0000.0640.0220.0000.0000.0000.0400.0180.0000.0040.0000.0220.0060.0080.0000.0160.0000.0000.0000.0190.0100.0190.0000.0080.0110.0000.0000.0000.0000.0120.0000.0200.0180.0110.0190.0220.0000.0000.0000.0000.0000.0530.0000.0000.0000.0210.0050.0000.000
States_CA0.0610.0000.0240.0000.0210.1030.0000.0920.0390.0390.0000.0000.0000.0000.0000.0110.0130.0000.0190.0000.0000.0000.0000.0000.0000.0260.0140.0000.0000.0000.0000.0200.0000.0270.0180.0130.0480.0000.0000.0000.0000.0000.0000.0320.0000.0670.0830.0400.0440.0641.0000.0550.0140.0000.0000.0830.0500.0000.0370.0340.0550.0380.0390.0300.0470.0270.0200.0110.0500.0410.0510.0270.0390.0420.0230.0300.0110.0340.0430.0310.0530.0490.0420.0500.0550.0000.0000.0360.0090.0250.1060.0320.0300.0000.0540.0370.0070.032
States_CO0.0000.0000.0000.0340.0210.0160.0000.0120.0000.0000.0510.0000.0000.0340.0140.0070.0180.0000.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0130.0000.0000.0000.0000.0060.0000.0000.0000.0000.0330.0000.0040.0220.0551.0000.0000.0000.0000.0330.0120.0000.0000.0000.0160.0000.0000.0000.0090.0000.0000.0000.0120.0000.0130.0000.0000.0000.0000.0000.0000.0000.0010.0000.0140.0110.0000.0120.0160.0000.0000.0000.0000.0000.0450.0000.0000.0000.0150.0000.0000.000
States_CT0.0000.0950.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0140.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.000
States_DC0.0000.0000.0000.0000.0490.0000.0910.0130.0000.0000.0000.0000.0000.0320.0000.0000.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_DE0.0000.0000.0000.0000.0000.0000.0000.0130.0740.0740.0000.0000.0000.0160.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_FL0.0150.0000.0000.0350.0570.0000.0000.0000.0220.0220.0150.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0230.0000.0150.0180.0000.0260.0000.0000.0000.0230.0000.0000.0160.0000.0540.0210.0240.0400.0830.0330.0000.0000.0001.0000.0290.0000.0180.0150.0330.0190.0200.0120.0270.0080.0000.0000.0300.0220.0300.0080.0210.0230.0000.0120.0000.0150.0240.0130.0310.0290.0230.0300.0330.0000.0000.0170.0000.0040.0700.0140.0120.0000.0320.0190.0000.014
States_GA0.0000.0000.0000.0000.0000.0000.0540.0220.0150.0150.0000.0000.0000.0110.0060.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0290.0000.0100.0360.0330.0000.0000.0000.0000.0000.0000.0000.0290.0000.0000.0180.0500.0120.0000.0000.0000.0291.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0070.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0060.0000.0070.0120.0000.0000.0000.0000.0000.0410.0000.0000.0000.0110.0000.0000.000
States_HI0.0000.0580.0000.2860.0740.0390.0000.0440.0000.0000.0150.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_IA0.0000.0000.0000.0000.0000.0260.0000.0300.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0040.0370.0000.0000.0000.0000.0180.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0290.0000.0000.0000.0000.0000.0000.000
States_ID0.0000.0000.0000.0490.0000.0110.0000.0130.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0420.0000.0000.0000.0000.0000.0000.0000.0300.0200.0130.0000.0220.0000.0000.0150.0000.0000.0000.0340.0000.0000.0000.0000.0150.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.000
States_IL0.0170.0000.0000.0000.0000.0260.0000.0270.0300.0300.0300.0000.0000.0000.0000.0070.0180.0000.0000.0000.0060.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0010.0000.0000.0000.0160.0140.0000.0110.0000.0440.0230.0000.0000.0000.0000.0330.0000.0040.0220.0550.0160.0000.0000.0000.0330.0120.0000.0000.0001.0000.0000.0000.0000.0090.0000.0000.0000.0120.0000.0130.0000.0000.0000.0000.0000.0000.0000.0010.0000.0140.0110.0000.0120.0160.0000.0000.0000.0000.0000.0450.0000.0000.0000.0150.0000.0000.000
States_IN0.0000.0000.0000.0000.0570.0000.0000.0030.0000.0000.0050.0000.0000.0300.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0060.0380.0000.0000.0000.0000.0190.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0000.0000.000
States_KS0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0190.0000.0000.0000.0160.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0080.0390.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.000
States_KY0.0000.0000.0000.0000.0000.0000.0000.0000.0090.0090.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0400.0000.0000.0000.0000.0000.0400.0000.0310.0000.0000.0000.0000.0000.0030.0110.0000.0000.0000.0000.0120.0000.0000.0000.0300.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.000
States_LA0.0000.0000.0000.0000.0000.0240.0000.0200.0110.0110.0000.0000.0000.0000.0400.0000.0620.0000.0540.0000.0000.0000.0000.0210.0000.0690.0000.0000.0000.0000.0000.0310.0000.0000.0000.0250.0070.0140.0000.0000.0110.0390.0000.0000.0000.0000.0270.0000.0000.0160.0470.0090.0000.0000.0000.0270.0000.0000.0000.0000.0090.0000.0000.0001.0000.0000.0000.0000.0020.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0020.0090.0000.0000.0000.0000.0000.0380.0000.0000.0000.0080.0000.0000.000
States_MA0.0000.0000.1100.1620.0340.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0140.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0070.0000.0000.0000.0270.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.000
States_MD0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0340.0000.0360.0000.0000.0000.0190.0300.0000.0220.0000.0000.0000.0000.0000.0070.0050.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.000
States_ME0.0000.0260.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0250.0000.0000.0000.0040.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_MI0.0000.0000.0000.0000.0270.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0130.0000.0030.0000.0000.0000.0000.0120.0000.0210.0170.0000.0000.0000.0000.0210.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0180.0000.0000.0290.0000.0000.0190.0500.0120.0000.0000.0000.0300.0070.0000.0000.0000.0120.0000.0000.0000.0020.0000.0000.0001.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0060.0000.0080.0120.0000.0000.0000.0000.0000.0410.0000.0000.0000.0110.0000.0000.000
States_MN0.0000.0000.0000.0000.0000.0040.0100.0210.0000.0000.0000.0000.0000.0000.0000.0000.0340.0000.0120.0000.0000.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0110.0000.0090.0000.0000.0220.0000.0000.0100.0410.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0000.0000.0000.000
States_MO0.0000.0000.0000.0000.0000.0360.0410.0100.0310.0310.0000.0080.0000.0090.0080.0000.0140.0000.0000.0110.0000.0300.0000.0500.0000.0130.0000.0000.0000.0000.0000.0170.0150.0000.0000.0310.0000.0000.0000.0000.0000.0290.0000.0000.0290.0000.0300.0000.0000.0190.0510.0130.0000.0000.0000.0300.0080.0000.0000.0000.0130.0000.0000.0000.0040.0000.0000.0000.0090.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0070.0000.0090.0130.0000.0000.0000.0000.0000.0420.0000.0000.0000.0120.0000.0000.000
States_MS0.0140.0000.0000.0000.0000.0390.0000.0300.0000.0000.0220.0000.0000.0000.0000.0000.1040.0000.0000.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.0000.0070.0000.0420.0180.0140.0000.0000.0000.0000.0410.0770.0000.0000.0000.0000.0070.0000.0000.0000.0270.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.000
States_MT0.0000.0380.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0320.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0330.0000.0120.0080.0000.0200.0000.0000.0080.0390.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.000
States_NC0.0000.0000.0000.0000.0210.0000.0470.0120.0000.0000.0040.0000.0340.0000.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0110.0000.0000.0180.0130.0000.0000.0000.0000.0230.0000.0000.0110.0420.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0000.0000.0000.000
States_ND0.0000.0000.0000.0000.0000.0390.0000.0310.0070.0070.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0000.0240.0000.0000.0020.0050.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.000
States_NE0.0000.0000.1530.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0420.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0300.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.000
States_NH0.0000.0000.0000.0000.0680.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0550.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0330.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_NJ0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0310.0000.0000.0210.0000.0000.0150.0000.0000.0000.0340.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.000
States_NM0.0340.0000.0000.0000.0450.0000.0110.0150.0000.0000.0000.0000.0000.0000.0160.0430.0000.0000.0250.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0030.0070.0000.0000.0000.0000.0120.0000.0000.0070.0000.0000.0230.0000.0000.0120.0430.0010.0000.0000.0000.0240.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0340.0000.0000.0000.0000.0000.0000.000
States_NV0.0000.0000.0000.0000.0000.0310.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0500.0000.0220.0000.0240.0390.0000.0000.0000.0000.0000.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0370.0000.0000.0120.0000.0000.0000.0310.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.000
States_NY0.0990.0940.0970.0000.0280.0400.0160.0270.0190.0190.0030.0050.0000.0000.0000.0000.0260.0000.0350.0000.0300.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0210.0200.0000.0140.0400.0170.0230.0130.0000.0000.0250.0360.0000.0000.0000.0310.0000.0000.0200.0530.0140.0000.0000.0000.0310.0100.0000.0000.0000.0140.0000.0000.0000.0070.0000.0000.0000.0100.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0090.0000.0100.0140.0000.0000.0000.0000.0000.0430.0000.0000.0000.0130.0000.0000.000
States_OH0.0000.0180.0000.0250.0000.0000.0000.0000.0430.0430.0000.0000.0000.0000.0000.0000.0110.0000.0240.0140.0000.0000.0000.0000.0000.0080.0000.0000.0000.0510.0000.0000.0000.0000.0000.0130.0090.0000.0000.0000.0060.0000.0000.0000.0000.0000.0290.0000.0000.0180.0490.0110.0000.0000.0000.0290.0060.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0060.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0091.0000.0000.0060.0110.0000.0000.0000.0000.0000.0400.0000.0000.0000.0100.0000.0000.000
States_OK0.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0290.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0580.0000.0000.0000.0000.0000.0180.0000.0000.0000.0160.0060.0000.0000.0110.0000.0230.0000.0000.0110.0420.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0000.0000.0000.000
States_OR0.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0440.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.0070.0000.0000.0000.0110.0110.0000.0000.0000.0110.0000.0000.0000.0290.0000.0000.0190.0500.0120.0000.0000.0000.0300.0070.0000.0000.0000.0120.0000.0000.0000.0020.0000.0000.0000.0080.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0060.0001.0000.0120.0000.0000.0000.0000.0000.0410.0000.0000.0000.0110.0000.0000.000
States_PA0.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0100.0000.0070.0180.0590.0000.0000.0000.0000.0460.0030.0000.0000.0000.0000.0000.0000.0000.0360.0360.0000.0360.0000.0000.0090.0000.0000.0000.0000.0000.0000.0090.0000.0330.0000.0030.0220.0550.0160.0000.0000.0000.0330.0120.0000.0000.0000.0160.0000.0000.0000.0090.0000.0000.0000.0120.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0110.0000.0121.0000.0000.0000.0000.0000.0000.0450.0000.0000.0000.0150.0000.0000.000
States_PR0.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0130.0000.0000.0000.0460.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_RI0.0000.4050.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0020.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0420.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_SC0.0000.0000.0000.0000.0440.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0050.0000.0000.0000.0140.0000.0170.0000.0000.0000.0360.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.000
States_SD0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0060.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
States_TN0.0000.0000.0000.0910.0270.0120.0140.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0030.0000.0000.0000.0250.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0170.0000.0000.0000.0000.0000.0000.000
States_TX0.0550.0000.0000.0510.0380.0000.0000.0000.0140.0140.0290.0000.0040.0080.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0170.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0700.0310.0350.0530.1060.0450.0020.0000.0000.0700.0410.0000.0290.0260.0450.0300.0310.0230.0380.0200.0120.0000.0410.0330.0420.0200.0310.0330.0150.0230.0000.0260.0340.0230.0430.0400.0330.0410.0450.0000.0000.0280.0000.0171.0000.0240.0230.0000.0440.0290.0000.025
States_UT0.0420.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0080.0000.0200.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0280.0000.0170.0000.0000.0140.0000.0000.0000.0320.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0241.0000.0000.0000.0000.0000.0000.000
States_VA0.0560.0000.0000.0000.0000.0000.0000.0000.0370.0370.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0190.0000.0070.0030.0000.0340.0000.0060.0090.0000.0000.0210.0000.0000.0120.0000.0000.0000.0300.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0001.0000.0000.0000.0000.0000.000
States_VT0.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.000
States_WA0.0180.0120.0000.0000.0490.0000.0030.0000.0240.0240.0130.0000.0000.0000.0000.0000.0060.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0320.0000.0000.0210.0540.0150.0000.0000.0000.0320.0110.0000.0000.0000.0150.0000.0000.0000.0080.0000.0000.0000.0110.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0100.0000.0110.0150.0000.0000.0000.0000.0000.0440.0000.0000.0001.0000.0000.0000.000
States_WI0.0000.0000.0000.0000.0000.0000.0000.0000.0320.0320.0230.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0090.0000.0000.0000.0000.0000.0130.0000.0000.0000.0090.0000.0000.0000.0000.0080.0000.0000.0040.0050.0450.0190.0000.0000.0050.0370.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0290.0000.0000.0000.0001.0000.0000.000
States_WV0.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
States_WY0.0000.1590.1440.0360.0280.0000.0000.0000.0190.0190.0410.0000.0000.0000.0570.0000.0080.0530.0000.0000.0000.0000.0000.0140.0000.0190.0000.0000.0000.0000.0000.0590.0000.0000.0000.0100.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0320.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0001.000

Missing values

2023-06-01T13:54:53.983812image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-06-01T13:54:55.167733image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Number.of.EnginesTotal.Fatal.InjuriesTotal.Serious.InjuriesTotal.Minor.InjuriesTotal.UninjuredAircraft.damage_DestroyedAircraft.damage_MinorAircraft.damage_SubstantialAmateur.Built_NoAmateur.Built_YesEngine.Type_reciprocatingEngine.Type_turbo fanEngine.Type_turbo jetEngine.Type_turbo propEngine.Type_turbo shaftEngine.Type_unknownPurpose.of.flight_Aerial ApplicationPurpose.of.flight_Aerial ObservationPurpose.of.flight_BusinessPurpose.of.flight_Executive/corporatePurpose.of.flight_FerryPurpose.of.flight_Flight TestPurpose.of.flight_Glider TowPurpose.of.flight_InstructionalPurpose.of.flight_Other Work UsePurpose.of.flight_PersonalPurpose.of.flight_PositioningPurpose.of.flight_Public AircraftPurpose.of.flight_Public Aircraft - FederalPurpose.of.flight_Public Aircraft - LocalPurpose.of.flight_SkydivingPurpose.of.flight_UnknownWeather.Condition_IMCWeather.Condition_UNKWeather.Condition_VMCBroad.phase.of.flight_ApproachBroad.phase.of.flight_ClimbBroad.phase.of.flight_CruiseBroad.phase.of.flight_DescentBroad.phase.of.flight_Go-aroundBroad.phase.of.flight_LandingBroad.phase.of.flight_ManeuveringBroad.phase.of.flight_StandingBroad.phase.of.flight_TakeoffBroad.phase.of.flight_TaxiBroad.phase.of.flight_UnknownStates_AKStates_ALStates_ARStates_AZStates_CAStates_COStates_CTStates_DCStates_DEStates_FLStates_GAStates_HIStates_IAStates_IDStates_ILStates_INStates_KSStates_KYStates_LAStates_MAStates_MDStates_MEStates_MIStates_MNStates_MOStates_MSStates_MTStates_NCStates_NDStates_NEStates_NHStates_NJStates_NMStates_NVStates_NYStates_OHStates_OKStates_ORStates_PAStates_PRStates_RIStates_SCStates_SDStates_TNStates_TXStates_UTStates_VAStates_VTStates_WAStates_WIStates_WVStates_WY
71.00.00.00.02.0001101000000000000001000000001000000001000000000000000000000000000000000000000000000000001000
82.00.00.00.02.0001101000000010000000000000100000001000000000000000000000000000000000000100000000000000000000
121.00.00.01.00.0100101000000000000001000000100001000000000000000000000000001000000000000000000000000000000000
131.01.00.00.00.0100101000000000000001000000100000000001000000000000000000000000000000000000000000000010000000
141.01.00.00.00.0100101000000000000001000000100001000000000000000000000000000000000000000000001000000000000000
151.02.00.00.00.0100101000000000000001000000100001000000000010000000000000000000000000000000000000000000000000
161.00.00.00.01.0100101000000000000001000000100000000000100000000000000000000000000000000000000000000001000000
171.03.00.00.00.0100101000000000000001000000001000000000011000000000000000000000000000000000000000000000000000
181.00.00.00.01.0001101000000000000001000000001000000000100000000000000000000000000000000000000010000000000000
191.00.00.00.02.0001101000000000000001000000001001000000000000000001000000000000000000000000000000000000000000
Number.of.EnginesTotal.Fatal.InjuriesTotal.Serious.InjuriesTotal.Minor.InjuriesTotal.UninjuredAircraft.damage_DestroyedAircraft.damage_MinorAircraft.damage_SubstantialAmateur.Built_NoAmateur.Built_YesEngine.Type_reciprocatingEngine.Type_turbo fanEngine.Type_turbo jetEngine.Type_turbo propEngine.Type_turbo shaftEngine.Type_unknownPurpose.of.flight_Aerial ApplicationPurpose.of.flight_Aerial ObservationPurpose.of.flight_BusinessPurpose.of.flight_Executive/corporatePurpose.of.flight_FerryPurpose.of.flight_Flight TestPurpose.of.flight_Glider TowPurpose.of.flight_InstructionalPurpose.of.flight_Other Work UsePurpose.of.flight_PersonalPurpose.of.flight_PositioningPurpose.of.flight_Public AircraftPurpose.of.flight_Public Aircraft - FederalPurpose.of.flight_Public Aircraft - LocalPurpose.of.flight_SkydivingPurpose.of.flight_UnknownWeather.Condition_IMCWeather.Condition_UNKWeather.Condition_VMCBroad.phase.of.flight_ApproachBroad.phase.of.flight_ClimbBroad.phase.of.flight_CruiseBroad.phase.of.flight_DescentBroad.phase.of.flight_Go-aroundBroad.phase.of.flight_LandingBroad.phase.of.flight_ManeuveringBroad.phase.of.flight_StandingBroad.phase.of.flight_TakeoffBroad.phase.of.flight_TaxiBroad.phase.of.flight_UnknownStates_AKStates_ALStates_ARStates_AZStates_CAStates_COStates_CTStates_DCStates_DEStates_FLStates_GAStates_HIStates_IAStates_IDStates_ILStates_INStates_KSStates_KYStates_LAStates_MAStates_MDStates_MEStates_MIStates_MNStates_MOStates_MSStates_MTStates_NCStates_NDStates_NEStates_NHStates_NJStates_NMStates_NVStates_NYStates_OHStates_OKStates_ORStates_PAStates_PRStates_RIStates_SCStates_SDStates_TNStates_TXStates_UTStates_VAStates_VTStates_WAStates_WIStates_WVStates_WY
612821.01.00.00.00.0001101000000000000001000000100100000000000000000000000000000000000000000000000000000000100000
612861.03.00.00.00.0100101000000000000001000000001001000000000000000000000000000000000000000000000000000001000000
612881.01.00.00.00.0001011000000000000001000000001000000001000000000000000000000000000001000000000000000000000000
612931.00.00.02.00.0001101000000000000001000000001001000000000000000001000000000000000000000000000000000000000000
613361.00.00.00.01.0001101000000000000001000000001000000001000000000000000000000000000000000100000000000000000000
613371.00.00.02.00.0001101000000000000001000000001000000001000000000001000000000000000000000000000000000000000000
613401.00.00.00.04.0010101000000000000001000000001010000000000000010000000000000000000000000000000000000000000000
613441.00.01.00.00.0001011000000000000001000000001001000000000000100000000000000000000000000000000000000000000000
613491.02.00.00.00.0100011000000000000001000000001000000100000000000000000000000000000000000000000000000010000000
613511.03.00.00.00.0001100000100000000010000000001000000100000100000000000000000000000000000000000000000000000000

Duplicate rows

Most frequently occurring

Number.of.EnginesTotal.Fatal.InjuriesTotal.Serious.InjuriesTotal.Minor.InjuriesTotal.UninjuredAircraft.damage_DestroyedAircraft.damage_MinorAircraft.damage_SubstantialAmateur.Built_NoAmateur.Built_YesEngine.Type_reciprocatingEngine.Type_turbo fanEngine.Type_turbo jetEngine.Type_turbo propEngine.Type_turbo shaftEngine.Type_unknownPurpose.of.flight_Aerial ApplicationPurpose.of.flight_Aerial ObservationPurpose.of.flight_BusinessPurpose.of.flight_Executive/corporatePurpose.of.flight_FerryPurpose.of.flight_Flight TestPurpose.of.flight_Glider TowPurpose.of.flight_InstructionalPurpose.of.flight_Other Work UsePurpose.of.flight_PersonalPurpose.of.flight_PositioningPurpose.of.flight_Public AircraftPurpose.of.flight_Public Aircraft - FederalPurpose.of.flight_Public Aircraft - LocalPurpose.of.flight_SkydivingPurpose.of.flight_UnknownWeather.Condition_IMCWeather.Condition_UNKWeather.Condition_VMCBroad.phase.of.flight_ApproachBroad.phase.of.flight_ClimbBroad.phase.of.flight_CruiseBroad.phase.of.flight_DescentBroad.phase.of.flight_Go-aroundBroad.phase.of.flight_LandingBroad.phase.of.flight_ManeuveringBroad.phase.of.flight_StandingBroad.phase.of.flight_TakeoffBroad.phase.of.flight_TaxiBroad.phase.of.flight_UnknownStates_AKStates_ALStates_ARStates_AZStates_CAStates_COStates_CTStates_DCStates_DEStates_FLStates_GAStates_HIStates_IAStates_IDStates_ILStates_INStates_KSStates_KYStates_LAStates_MAStates_MDStates_MEStates_MIStates_MNStates_MOStates_MSStates_MTStates_NCStates_NDStates_NEStates_NHStates_NJStates_NMStates_NVStates_NYStates_OHStates_OKStates_ORStates_PAStates_PRStates_RIStates_SCStates_SDStates_TNStates_TXStates_UTStates_VAStates_VTStates_WAStates_WIStates_WVStates_WY# duplicates
1841.00.00.00.02.000110100000000000000100000000100000100000000010000000000000000000000000000000000000000000000016
1091.00.00.00.01.000110100000000000010000000000100000100000000010000000000000000000000000000000000000000000000012
1591.00.00.00.02.000110100000000000000100000000100000000100100000000000000000000000000000000000000000000000000011
611.00.00.00.01.000110100000000000000100000000100000100000000000000100000000000000000000000000000000000000000010
631.00.00.00.01.000110100000000000000100000000100000100000000010000000000000000000000000000000000000000000000010
971.00.00.00.01.000110100000000000010000000000100000100000000000000000000000000000100000000000000000000000000010
661.00.00.00.01.00011010000000000000010000000010000010000010000000000000000000000000000000000000000000000000009
431.00.00.00.01.00011010000000000000010000000010000000010010000000000000000000000000000000000000000000000000008
451.00.00.00.01.00011010000000000000010000000010000010000000000000000000000000000000000000000000000000100000008
1061.00.00.00.01.00011010000000000001000000000010000010000000000000010000000000000000000000000000000000000000008